Dataset Information

Tryptic shaving of Staphylococcus aureus

ABSTRACT: Surface proteins of Gram-positive bacteria are critical for adherence to host tissues, evasion of the immune system, and interaction with the environment. They can be utilized as biomarkers in diagnostics, for vaccine development, and as therapeutic targets due to their accessibility and role in pathogenicity. If utilized as diagnostic targets, surface biomarkers should be highly conserved across different strains of the pathogen, unique to the species to avoid cross-reactivity, abundantly expressed on the bacterial surface, and accessible to antibodies or detection reagents. Mass spectrometry-based proteomics methods has advanced the studies of surface proteins, often in combination with selective enrichment strategies such as tryptic “shaving”. In this study, 11 clinical strains of Staphylococcus aureus underwent tryptic shaving to identify common surface proteins. Further bioinformatics analysis confirmed that these proteins are encoded in the core genome of numerous S. aureus strains and contained species-specific peptides. In silico analysis identified 26 k-mer peptides in 15 surface proteins, with structural accessibility to detection agents, making them the ideal targets for molecular diagnostics or as linear epitope targets for vaccine development or therapeutics

INSTRUMENT(S):

ORGANISM(S): Bacteria Staphylococcus Aureus

SUBMITTER: Ema Svetlicic

LAB HEAD: Ivan Mijakovic

PROVIDER: PXD061994 | Pride | 2025-09-15

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	20230504_MK_E1200_MVL_FAIMS_2CV_15cm_70min_1687_DDA_8ul_peptides.txt	Txt
	20230504_MK_E1200_MVL_FAIMS_2CV_15cm_70min_1687_DDA_8ul_proteins.txt	Txt
	transfer_81379_files_5dfc54f2.zip	Other

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Publications

Mass Spectrometry-Based Analysis of Surface Proteins in <i>Staphylococcus aureus</i> Clinical Strains: Identification of Promising k-mer Targets for Diagnostics.

Svetlicic Ema E Alarcon Leonarda A LA Karlsson Roger R Jers Carsten C Mijakovic Ivan I

Journal of proteome research 20250807 9

Surface proteins of Gram-positive bacteria are critical for adherence to host tissues, evasion of the immune system, and interaction with the environment. They can be utilized as biomarkers in diagnostics, for vaccine development, and as therapeutic targets due to their accessibility and role in pathogenicity. If utilized as diagnostic targets, surface biomarkers should be highly conserved across different strains of the pathogen, unique to the species to avoid cross-reactivity, abundantly expre ...[more]

PMID: 40772958

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Project description:Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the hostM-bM-^@M-^Ys inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 95 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.82). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.94, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues. To create a host gene expression-based classifier for S. aureus infection, mice from a variety of experimental conditions were utilized. Seven different strains of inbred mice (n=187 total) were challenged with four different S. aureus strains via intraperitoneal inoculation and sacrificed at various time points as described in Methods. The comparator group for model derivation included 50 A/J or C57BL/6J mice inoculated with E. coli (O18:K1:H7) as well as 54 uninfected mice. Next, the murine S. aureus classifier was externally validated in outbred CD-1 mice with S. aureus infection (Sanger 476 or USA300), E. coli infection (O18:K1:H7), or uninfected controls (10 animals per condition). Method: All experiments were performed on mice 6-8 weeks old. For the murine S. aureus predictor, seven inbred mouse strains (3 mice/strain: 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C57BL/6J, C3H/HeJ, and NOD/LtJ) were IP inoculated with 107 CFU/g of S. aureus Sanger476, euthanized at 2h after injection, and bled. This was repeated using four different S. aureus strains (USA100, USA300, MW2, and Sanger476) in A/J mice (n=3 per S. aureus strain). For time series experiments, both A/J and C57BL/6J mouse strains were IP inoculated with S. aureus Sanger476 as above, and sacrificed at 2, 4, 6, and 12h after injection (n=5 per time point).

Dataset Information

Tryptic shaving of Staphylococcus aureus

Dataset's files

Publications

Mass Spectrometry-Based Analysis of Surface Proteins in <i>Staphylococcus aureus</i> Clinical Strains: Identification of Promising k-mer Targets for Diagnostics.

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OmicsDI is part of the ELIXIR infrastructure

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Dataset Information

Tryptic shaving of Staphylococcus aureus

Dataset's files

Publications

Mass Spectrometry-Based Analysis of Surface Proteins in &lt;i&gt;Staphylococcus aureus&lt;/i&gt; Clinical Strains: Identification of Promising k-mer Targets for Diagnostics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Mass Spectrometry-Based Analysis of Surface Proteins in <i>Staphylococcus aureus</i> Clinical Strains: Identification of Promising k-mer Targets for Diagnostics.